Electronic apparatus for responding to question using multi chat-bot and control method thereof

ABSTRACT

An electronic apparatus includes a memory storing instructions, a plurality of chat-bots for responding to a plurality of questions, and a question classification model trained to identify a chat-bot among the plurality of chat-bots for responding to an input question, and a processor configured to execute the instructions to input the input question into the question classification model, the question classification model outputting a first chat-bot among the plurality of chat-bots for responding to the input question, acquire a first response for the input question, through the outputted first chat-bot, based on the acquired first response comprising information of a function that can be performed at the electronic apparatus, generate a question requesting to perform the function, and input the generated question into the question classification model, the question classification model outputting a second chat-bot among the plurality of chat-bots for responding to the generated question.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a bypass continuation of International ApplicationNo. PCT/KR2021/012270, filed on Sep. 9, 2021, which is based on andclaims priority to Korean Patent Application No. 10-2020-0130313, filedon Oct. 8, 2020, in the Korean Intellectual Property Office, thedisclosures of which are incorporated by reference herein in theirentireties.

BACKGROUND 1. Field

The disclosure relates to an electronic apparatus that responds to aquestion, and more particularly, to an electronic apparatus thatprovides a response by selectively using a plurality of chat-bots.

2. Description of Related Art

In a multi chat-bot environment in which a plurality of chat-botsproviding different services from one another are used, if a user'squestion is input, a response and a function are provided through anyone chat-bot selected.

In case a response provided through a selected chat-bot includesinformation on a function, even though the function can be automaticallyperformed through another chat-bot, only the response of the selectedchat-bot is provided. As a result, an inconvenient circumstance whereina user has to directly perform the function may occur.

This is due to the fact that, as each chat-bot provides a differentservice, there are many cases wherein each chat-bot is developed/updatedindependently.

Even though such a problem could be overcome if responses/functions ofdifferent chat-bots are interlocked with one another one by one, in thiscase, there may be a problem that the process of developing/updatingeach chat-bot becomes too cumbersome.

FIG. 1 is a diagram for illustrating an example of an operation of amulti chat-bot environment according to the related art.

FIG. 1 illustrates a user 10 of an electronic apparatus (ex. asmartphone) and an artificial intelligence (AI) assistant 20 thatprovides services based on multi chat-bots through the electronicapparatus.

The AI assistant 20 may be defined as a voice assistant that providescomprehensive services, and referring to FIG. 1, the Al assistant 20 mayuse a customer service chat-bot 20-1, a settings chat-bot 20-2, aweather chat-bot 20-3, etc.

Referring to FIG. 1, in case the user 10 asked a question “The Internetconnection is not working” 11, the customer service chat-bot 20-1 amongthe chat-bots of the AI assistant 20 may be selected.

Then, the customer service chat-bot 20-1 may provide a response 21 tothe user's question 11 as in FIG. 1.

Referring to FIG. 1, the customer service chat-bot 20-1 just provides aresponse 21 informing what is the currently needed function (mobiledata>turn on) is, and it cannot directly perform the correspondingfunction.

In this case, even if it is possible to automatically provide thecorresponding function (mobile data>turn on) through the settingchat-bot 20-2, it may be difficult to use the setting chat-bot 20-2 thatwas not selected.

As a result, the user cannot help activating the corresponding function(mobile data>turn on) directly through a manual operation for theelectronic apparatus.

SUMMARY

Provided are an electronic apparatus that effectively combines andprovides responses and functions of chat-bots that are independentlydeveloped, and a control method thereof.

Further, provided are an electronic apparatus that can provideappropriate responses/functions while optimizing utilization of modulecomponents by repetitively using a question classification model thatselects a chat-bot for responding to a question, and a control methodthereof.

Further still, provided are an electronic apparatus that can effectivelycombine and provide responses/functions provided by chat-bots whilemaintaining the development environments of the respective chat-botsthat are professionally/independently developed/updated for respectiveservices, and a control method thereof.

Additional aspects will be set forth in part in the description thatfollows and, in part, will be apparent from the description, or may belearned by practice of the presented embodiments.

In accordance with an aspect of the disclosure, there is provided anelectronic apparatus including a memory storing instructions, aplurality of chat-bots for responding to a plurality of questions, and aquestion classification model trained to identify one among theplurality of chat-bots for responding to an input question, and aprocessor configured to execute the instructions to input the inputquestion into the question classification model, the questionclassification model outputting a first one among the plurality ofchat-bots for responding to the input question. The processor is furtherconfigured to execute the instructions to acquire a first response forthe input question, through the outputted first one among the pluralityof chat-bots, based on the acquired first response including informationof a function that can be performed at the electronic apparatus,generate a question requesting to perform the function, and input thegenerated question into the question classification model, the questionclassification model outputting a second one among the plurality ofchat-bots for responding to the generated question. The processor isfurther configured to execute the instructions to acquire a secondresponse for the generated question, through the outputted second oneamong the plurality of chat-bots, and provide a combined response to theinput question, based on the acquired first response and the acquiredsecond response.

The memory may further include information of a plurality of domainsrespectively mapped to the plurality of chat-bots, and the processor maybe further configured to execute the instructions to, through thequestion classification model, identify a first one among the pluralityof domains that is related to a text included in the input question, andbased on the information of the plurality of domains respectively mappedto the plurality of chat-bots, select the first one among the pluralityof chat-bots that is mapped to the identified first one among theplurality of domains.

The processor may be further configured to execute the instructions to,through the question classification model, identify a second one amongthe plurality of domains that is related to a text included in thegenerated question, and based on the information of the plurality ofdomains respectively mapped to the plurality of chat-bots, select thesecond one among the plurality of chat-bots that is mapped to theidentified second one among the plurality of domains.

The processor may be further configured to execute the instructions to,based on the acquired first response not including the information ofthe function that can be performed at the electronic apparatus, providea response to the input question, based on the acquired first response.

The memory may further include a list of functions that can be performedat the electronic apparatus, and the processor may be further configuredto execute the instructions to, based on the acquired first responseincluding information of a plurality of functions, identify at least oneamong the plurality of functions that can be performed at the electronicapparatus, based on the list, and generate the question requesting toperform the identified at least one among the plurality of functions.

The memory may further include a function selection model trained to,based on information of the plurality of functions being input, selectone or more among the plurality of functions that corresponds to theinput question, and the processor may be further configured to executethe instructions to input the information of the plurality of functionsincluded in the acquired first response, the list, and the inputquestion into the function selection model, the function selection modeloutputting the one or more among the plurality of functions thatcorresponds to the input question and can be performed at the electronicapparatus.

The processor may be further configured to execute the instructions to,based on identifying that there is not one among the plurality ofchat-bots for responding to the generated question, provide a responseto the input question, based on the acquired first response.

The processor may be further configured to execute the instructions to,based on the acquired first response and the acquired second response,generate the combined response including a question regarding whetherthe function can be performed, provide the generated combined response,and based on a request for performing the function being input as thecombined response is provided, perform the function, through the secondone among the plurality of chat-bots.

In accordance with an aspect of the disclosure, there is provided acontrol method of an electronic apparatus, the method includinginputting an input question into a question classification model trainedto identify one among a plurality of chat-bots for responding to theinput question, the question classification model outputting a first oneamong the plurality of chat-bots for responding to the input question,acquiring a first response for the input question, through the outputtedfirst one among the plurality of chat-bots, and based on the acquiredfirst response including information of a function that can be performedat the electronic apparatus, generating a question requesting to performthe function. The control method further includes inputting thegenerated question into the question classification model, the questionclassification model outputting a second one among the plurality ofchat-bots for responding to the generated question, acquiring a secondresponse for the generated question, through the outputted second oneamong the plurality of chat-bots, and providing a combined response tothe input question, based on the acquired first response and theacquired second response.

The inputting the input question into the question classification modelmay include, through the question classification model, identifying afirst one among a plurality of domains that is related to a textincluded in the input question, the plurality of domains respectivelymapped to the plurality of chat-bots, and based on the information ofthe plurality of domains respectively mapped to the plurality ofchat-bots, selecting the first one among the plurality of chat-bots thatis mapped to the identified first one among the plurality of domains.

The inputting the generated question into the question classificationmodel may include, through the question classification model,identifying a second one among the plurality of domains that is relatedto a text included in the generated question, and based on theinformation of the plurality of domains respectively mapped to theplurality of chat-bots, selecting the second one among the plurality ofchat-bots that is mapped to the identified second one among theplurality of domains.

The control method may further include, based on the acquired firstresponse not including the information of the function that can beperformed at the electronic apparatus, providing a response to the inputquestion, based on the acquired first response.

The control method may further include, based on the acquired firstresponse including information of a plurality of functions, identifyingat least one among the plurality of functions that can be performed atthe electronic apparatus, based on a list of functions that can beperformed at the electronic apparatus, and generating the questionrequesting to perform the identified at least one among the plurality offunctions.

The identifying the at least one among the plurality of functions thatcan be performed at the electronic apparatus may include inputting theinformation of the plurality of functions included in the acquired firstresponse, the list, and the input question into a function selectionmodel trained to, based on information of the plurality of functionsbeing input, select one or more among the plurality of functions thatcorresponds to the input question, the function selection modeloutputting the one or more among the plurality of functions thatcorresponds to the input question and can be performed at the electronicapparatus.

The control method may further include, based on identifying that thereis not one among the plurality of chat-bots for responding to thegenerated question, providing a response to the input question, based onthe acquired first response.

BRIEF DESCRIPTION OF THE DRAWINGS

The above and other aspects, features, and advantages of embodiments ofthe disclosure will be more apparent from the following descriptiontaken in conjunction with the accompanying drawings, in which:

FIG. 1 is a diagram for illustrating an example of an operation of amulti chat-bot environment according to the related art;

FIG. 2 is a block diagram of a configuration and an operation of anelectronic apparatus according to an embodiment of the disclosure;

FIG. 3 is a diagram for illustrating a process wherein a questionclassification model according to an embodiment of the disclosure istrained;

FIG. 4 is a block diagram for illustrating an operation of an electronicapparatus according to an embodiment of the disclosure of acquiring aresponse of a selected chat-bot;

FIG. 5A is a block diagram of a function information extraction moduleof an electronic apparatus according to an embodiment of the disclosureof extracting/selecting function information from a chat-bot's response;

FIG. 5B is a diagram for illustrating an operation of an electronicapparatus according to an embodiment of the disclosure of selecting atleast one function from a plurality of extracted functions;

FIG. 6 is a block diagram of a question generation module of anelectronic apparatus according to an embodiment of the disclosure ofgenerating a question requesting to perform an extracted/selectedfunction and using the question;

FIG. 7 is a diagram for illustrating an operation of an electronicapparatus according to an embodiment of the disclosure of combiningresponses output from different chat-bots;

FIG. 8 is a block diagram of a detailed configuration of an electronicapparatus according to various embodiments of the disclosure;

FIG. 9A is a block diagram for illustrating an operation of anelectronic apparatus of using a plurality of chat-bots stored in aserver according to an embodiment of the disclosure;

FIG. 9B is a block diagram for illustrating an operation of anelectronic apparatus of selectively using assistants stored in eachserver according to an embodiment of the disclosure;

FIG. 10 is a flowchart of a control method of an electronic apparatusaccording to an embodiment of the disclosure; and

FIG. 11 is a flowchart of a control method of an electronic apparatusaccording to another embodiment of the disclosure.

DETAILED DESCRIPTION

An electronic apparatus and a control method according to the disclosurecan effectively combine and provide responses and functions of chat-botsthat are independently developed.

Also, the electronic apparatus and the control method according to thedisclosure can provide responses/functions of a plurality of chat-botswhile optimizing utilization of module components by repetitively usinga question classification model that selects a chat-bot for respondingto a question.

In addition, the electronic apparatus and the control method accordingto the disclosure can effectively combine and provideresponses/functions provided by chat-bots while maintaining thedevelopment environments of the respective chat-bots that areprofessionally/independently developed/updated for respective services.

Before describing the disclosure in detail, the drafting format of thisspecification and the drawings will be described.

First, as terms used in this specification and the claims, general termswere selected in consideration of the functions in the variousembodiments of the disclosure. However, the terms may vary depending onthe intention of those skilled in the art, legal or technicalinterpretation, emergence of new technologies, etc. Also, there areterms that were designated by the applicant on his own, and in suchcases, the meaning of the terms will be interpreted as defined in thisspecification, and if there is no definition of the terms, the meaningof the terms will be interpreted based on the overall content of thisspecification and common technical knowledge in the pertinent technicalfield.

Also, the same reference numerals or symbols described in each drawingaccompanying this specification refer to components or elementssubstantially performing the same functions. For the convenience ofexplanation and understanding, the components or elements will bedescribed by using the same reference numerals or symbols in differentembodiments. That is, even if all components having the same referencenumerals are illustrated in a plurality of drawings, the plurality ofdrawings do not mean one embodiment.

In addition, in this specification and the claims, terms includingordinal numbers such as “the first” and “the second” may be used fordistinguishing components. Such ordinal numbers are used fordistinguishing the same or similar components from one another, and itis not intended that the meaning of terms is restrictively interpreteddue to use of such ordinal numbers. As an example, the order of use orthe order of arrangement, etc. of a component combined with such ordinalnumbers may not be restricted by the numbers. Depending on needs, eachordinal number may be used while being replaced with each other.

Further, in this specification, singular expressions include pluralexpressions, unless defined obviously differently in the context. Also,in the disclosure, terms such as “include” and “consist of” may beconstrued as designating that there are such characteristics, numbers,steps, operations, elements, components or a combination thereofdescribed in the specification, but not as excluding in advance theexistence or possibility of adding one or more of other characteristics,numbers, steps, operations, elements, components or a combinationthereof.

In addition, in the embodiments of the disclosure, terms such as “amodule,” “a unit,” “a part” and the like are for referring to elementsperforming at least one function or operation, and these elements may beimplemented as hardware or software, or as a combination of hardware andsoftware. Further, a plurality of “modules,” “units,” “parts” and thelike may be integrated into at least one module or chip and implementedas at least one processor, except when each of them needs to beimplemented as individual hardware.

Also, in the embodiments of the disclosure, the description that a partis connected with another part not only includes a case of directconnection, but also a case of indirect connection through anothermedium. In addition, the description that a part includes an elementmeans that another element may be further included, but not that anotherelement is excluded, unless there is an opposing description.

FIG. 2 is a block diagram of a configuration and an operation of anelectronic apparatus according to an embodiment of the disclosure.

Referring to FIG. 2, an electronic apparatus 100 includes at least onememory 110 and a processor 120. The electronic apparatus 100 may be aserver, a smartphone, an AI speaker, etc., but is not limited thereto.

The memory 110 may include a plurality of chat-bots.

A chat-bot means a chatting-robot, and it is a concept that includes anagent for providing at least one service through the electronicapparatus 100 based on communication with a user, or overall dataconstituting the agent.

The plurality of chat-bots included in the memory 110 may be divided invarious ways according to the types of services provided by theelectronic apparatus 100.

Here, a service may include a response provided with respect to a user'squestion, and depending on cases, a service may further include at leastone function of the electronic apparatus 100 that is provided accordingto a user's question.

In the plurality of chat-bots, a customer service chat-bot that respondsto overall questions of customers regarding the electronic apparatus 100may be included.

If a user's question regarding the manipulation, the state, the defect,etc. of the electronic apparatus 100 is input, the customer servicechat-bot may provide a response to the input question.

In the plurality of chat-bots, a setting chat-bot that manages a usersetting for the electronic apparatus 100 may be included.

If a user's question for identifying the setting states for various usersetting items of the electronic apparatus 100 (ex. data communicationOn/Off, Wi-Fi On/Off, power saving mode On/Off, access authority forinformation of an app, etc.) is input, the setting chat-bot may providea response to the input question.

Also, the setting chat-bot may perform a function of changing thesetting state of at least one setting item according to a user'srequest.

In the plurality of chat-bots, a weather chat-bot that provides aservice of managing weather information may be included.

The weather chat-bot may provide a response to a user's questioninquiring about the weather. Alternatively, the weather chat-bot mayperform a function of providing the current weather to a user perpredetermined period.

As described above, the plurality of chat-bots may include chat-botsthat provide various services, and are not limited to the aforementionedexamples.

Each chat-bot may respond to a user's question related to a serviceprovided by the chat-bot. For this, a chat-bot may include a naturallanguage processing module for understanding the meaning of a text inputby a user, a question-response module for generating a separate text forresponding to an input text, etc.

Here, the natural language processing module may use an artificialintelligence model trained to understand various keywords related to aservice provided by a chat-bot.

Also, the question-response module may use an artificial intelligencemodel trained to, if a question is input, provide an appropriateresponse thereto through various questions-responses related to aservice provided by a chat-bot.

Each chat-bot may include a function processing module for providing atleast one function related to the service provided by the chat-bot.

For this, a function processing module of a chat-bot may includeinformation on a function that can be performed at the electronicapparatus through the chat-bot.

As an example, a function processing module of a chat-bot may include atleast one instruction that makes a function of the electronic apparatus100 activated by being executed by the processor 120 of the electronicapparatus 100.

If a keyword related to a function provided by a chat-bot is extractedfrom a user's question/request that was input, the function processingmodule of the chat-bot may perform a function related to the extractedkeyword.

As an example, if a user's request (ex. start the power saving mode) isinput, the aforementioned setting chat-bot may extract keywords such as“the power saving mode,” “start,” etc. from the user's request.

Then, the setting chat-bot may be implemented to generate an instructionfor activating the power saving mode of the electronic apparatus 100 byusing the extracted keywords. As a result, the power saving mode of theelectronic apparatus 100 may be activated.

The plurality of chat-bots included in the memory 110 may be included inone assistant. Here, the assistant may mean a comprehensive agent thatprovides various services through the electronic apparatus 100 based oncommunication with a user, such as Bixby.

That is, the plurality of services (responses, functions) providedthrough the plurality of chat-bots may be included in the comprehensiveservice provided by the assistant.

Although an embodiment wherein the plurality of chat-bots are includedin the memory 110 of the electronic apparatus 100 was illustratedthrough FIG. 2, the electronic apparatus 100 may use a plurality ofchat-bots stored in an external server. A detailed embodiment in thisregard will be described later through FIG. 9A and FIG. 9B, etc.

The memory 110 may include a question classification model trained todetermine a chat-bot for responding to an input question among aplurality of chat-bots. The question classification model may include atleast one artificial intelligence model implemented in the form of aclassifier.

As an example, the question classification model may be trained with alarge number of questions as input data, and chat-bots for responding tothe large number of respective questions as output data.

As an example, the question classification model may identify a domainmapped to an input question, and select a chat-bot mapped to theidentified domain among the plurality of chat-bots.

A domain may be defined through texts corresponding to variouswords/sentences. A domain may include information on texts related to aservice provided by at least one chat-bot.

Here, domains may be divided into various categories related to servicesprovided by each chat-bot such as music, weather, news, sports,apparatus setting, customer service, etc., but the categories are notlimited thereto.

As an example, a music domain may include information on various wordsand sentences related to a music service, and a sports domain mayinclude information on various words and sentences related to a sportsservice.

The question classification model may be trained with a large number oftexts as input data, and domains mapped to the large number ofrespective texts as output data.

Here, the question classification model may be trained to convert atleast one text (word or sentence) included in an input question into avector, and select a domain having the biggest relevance to theconverted vector, but is not limited thereto.

In case a domain mapped to an input question is selected, the questionclassification model may determine a chat-bot mapped to the selecteddomain by using information on the plurality of domains mapped to theplurality of respective chat-bots stored in the memory 110.

As an example, in case a user's question inquiring about the gameschedule of a professional soccer league is input into the questionclassification model, the question classification model may identify adomain mapped to the question as a sports domain.

In this case, a sports information chat-bot mapped with respect to thesports domain may be determined as a chat-bot for responding to theuser's question.

Then, the processor 120 may provide a response to the user's question (:information on the game schedule) through the sports informationchat-bot.

Referring to FIG. 2, the processor 120 may include a questionclassification module 121, a chat-bot management module 122, a functioninformation extraction module 123, a question generation module 124,etc.

These modules may be implemented in the form of software or hardware.Alternatively, these modules may be implemented in a form of includingsoftware and hardware.

Hereinafter, detailed operations of these modules will be described withreference to FIG. 2.

The question classification module 121 is a module that selects achat-bot to respond to an input question when a question is input.

The question classification module 121 may select a chat-bot to providea response among the plurality of chat-bots stored in the memory 110through the aforementioned question classification model.

As an example, referring to FIG. 2, a user's question (ex. The Internetconnection is not working. What should I do?) may be input into theprocessor 120 in operation S11.

A case wherein the electronic apparatus 100 is implemented as a serveris assumed. In this case, a user's question may be input into asmartphone or an AI speaker in the form of a voice. Here, the smartphoneor the AI speaker may convert the input user voice into a text, andtransmit it to the electronic apparatus 100. In this case, the processor120 may receive the converted text through a communication interface ofthe electronic apparatus 100.

Alternatively, a case wherein the electronic apparatus 100 isimplemented as a smartphone or an AI speaker is assumed. In this case,if a user uttered a question, the user voice is input through amicrophone of the electronic apparatus 100, and the processor 120 mayacquire a text converted from the input user voice.

Here, the question classification module 121 may input the input user'squestion into the aforementioned question classification model, andselect a chat-bot 1 (ex. a customer service chat-bot) for responding tothe user's question (question 1) among the plurality of chat-bots.

As an example, the question classification module 121 may identify afirst domain (ex. a customer service domain) related to a text includedin the input user's question (question 1) among the plurality of domainsthrough the question classification model.

Then, the question classification module 121 may select the chat-bot 1(ex. the customer service chat-bot) mapped to the identified firstdomain among the plurality of chat-bots based on information on theplurality of domains respectively mapped to the plurality of chat-bots.

Then, the question classification module 121 may transmit information onthe selected chat-bot 1 to the chat-bot management module 122 inoperation S12.

The chat-bot management module 122 is a module for managing a pluralityof chat-bots stored in the memory 110.

The chat-bot management module 122 may input a question into at leastone chat-bot, and acquire a response output from the chat-bot into whichthe question was input.

Here, the chat-bot management module 122 may provide the acquiredresponse to the user.

Also, the chat-bot management module 122 may perform at least onefunction of the electronic apparatus 100 through at least one chat-bot.

Referring to FIG. 2, the chat-bot management module 122 may input auser's question into the chat-bot 1 selected by the questionclassification module 121.

In this case, a first response (ex. Did you check the mobile data orWi-Fi connection state? Setting>connection>data use>mobile data>turn on)of the selected chat-bot 1 regarding the user's question may be acquiredin operation S13.

The function information extraction module 123 is a module forextracting information on a function from a response output from atleast one chat-bot.

The function information extraction module 123 may extract informationon functions that can be performed by the electronic apparatus 100.

The function information extraction module 123 may include a keywordextraction module for extracting keywords related to a function from aresponse (text), and determine whether the extracted each keyword is afunction that can be performed at the electronic apparatus 100.

For this, the function information extraction module 123 may use a listfor functions that can be performed by the electronic apparatus 100.This list may have been stored in the memory 110 in advance.

The function information extraction module 123 may compare the extractedeach keyword with the functions in the aforementioned list.

As an example, referring to FIG. 2, the function information extractionmodule 123 may receive the first response of the chat-bot 1 from thechat-bot management module 122 in operation S13.

Then, the function information extraction module 123 may extractinformation on at least one function (ex. mobile data>turn on) that canbe performed at the electronic apparatus 100 from the first response ofthe chat-bot 1 in operation S14.

Here, in case information on a plurality of functions was extracted fromthe first response, the function information extraction module 123 mayselect at least one function among the plurality of functions. Adetailed embodiment in this regard will be described later through FIG.5A and FIG. 5B.

As described above, in case information on a function (ex. mobiledata>turn on) that can be performed at the electronic apparatus 100 isextracted/selected by the function information extraction module 123,the function information extraction module 123 may transmit theextracted/selected information on the function to the questiongeneration module 124 in operation S14.

In case the first response does not include information on a functionthat can be performed at the electronic apparatus 100, the processor 120may provide a response to a user's question based on the aforementionedfirst response. That is, the processor 120 may provide only theaforementioned first response.

As an example, in case the electronic apparatus 100 is a server, theprocessor 120 may transmit information on the first response to asmartphone or an AI speaker through the communication interface. In thiscase, the first response may be output in the form of a voice throughthe smartphone or the AI speaker.

As another example, in case the electronic apparatus 100 is a smartphoneor an AI speaker, the first response may be output in the form of avoice through the speaker of the electronic apparatus 100.

The question generation module 124 is a module for generating a question(Text) related to at least one function.

The question generation module 124 may generate a question by usinginformation on a function acquired through the function informationextraction module 123.

Here, the question generation module 124 may generate a questionrequesting to perform the function.

For this, the question generation module 124 may use a questiongeneration model including at least one artificial intelligence modelthat is trained to, if information on at least one function is input,generate a question (text) requesting to perform the input function.

As an example, referring to FIG. 2, the question generation module 124may generate a question (ex. Turn on the mobile data) requesting toperform the function (ex. mobile data>turn on) extracted from thefunction information extraction module 123, and transmit the generatedquestion to the question classification module 121 in operation S15.

In this case, the question classification module 121 may select achat-bot 2 (ex. a setting chat-bot) for responding to the generatedquestion. That is, the processor 120 may select the chat-bot 2 that canperform the function included in the first response by using thequestion classification module 121.

As an example, the question classification module 121 may identify asecond domain (ex. an apparatus setting domain) related to a textincluded in a generated question (question 2) among the plurality ofdomains through the question classification model.

Then, the question classification module 121 may select the chat-bot 2(ex. the setting chat-bot) mapped to the identified second domain amongthe plurality of chat-bots based on information on the plurality ofdomains respectively mapped to the plurality of chat-bots.

Then, the question classification module 121 may transmit information onthe selected chat-bot 2 to the chat-bot management module 122 inoperation S16.

Here, the chat-bot management module 122 may immediately perform thefunction (ex. turning on the mobile data) of the electronic apparatus100 requested by the generated question (ex. Turn on the mobile data) byusing the chat-bot 2.

Alternatively, the chat-bot management module 122 may acquire a secondresponse (ex. Shall I turn on the mobile data?) of the chat-bot 2regarding the generated question (ex. Turn on the mobile data), andprovide a response to the user's question (question 1) based on theaforementioned first response and second response in operation S17.

The processor 120 may generate a combined response for the input user'squestion (question 1) based on the first response and the secondresponse.

Here, the combined response may simply include the first response andthe second response, or it may be a new response wherein the firstresponse and the second response are fused.

As an example, the processor 120 may generate a combined response (ex.The mobile data should be turned on. Shall I turn on the mobile data?)including a question regarding whether to perform the function (ex.turning on the mobile data) extracted from the aforementioned firstresponse, based on the first response and the second response.

For this, the processor 120 may use at least one response generatormodel, and a detailed embodiment related thereto will be described laterthrough FIG. 7.

Then, the chat-bot management module 122 may provide the generatedcombined response.

As a combined response is provided, a user's request (question orinstruction) for performing an extracted function may be input.

For example, as a combined response such as “The mobile data should beturned on. Shall I turn on the mobile data?” is provided, a user'sresponse such as “Yes” may be received.

In this case, the chat-bot 2 (ex. the setting chat-bot) may perform theaforementioned function (ex. turning on the mobile data) according tothe user's response.

As described above, in case a response provided through a chat-botincludes information on a separate function, the electronic apparatus100 according to the disclosure may not immediately provide theresponse, but additionally acquire a response of another chat-bot thatcan perform the function.

As a result, responses acquired from a plurality of chat-bots may beprovided together, and thus there is an effect that a more effectiveresponse regarding a user's question can be provided with acorresponding function.

Hereinafter, with reference to FIG. 3 to FIG. 7, operations of each ofthe aforementioned modules will be described through more examples.

FIG. 3 is a block diagram for illustrating a process wherein a questionclassification model according to an embodiment of the disclosure istrained.

Referring to FIG. 3, the question classification module 121 may use aquestion classification model 310 trained to determine a domain matchedto an input question.

The question classification model 310 may be trained through questiontexts for training matched to each of various domains.

As an example, referring to FIG. 3, the question classification model310 may be trained through questions 301 related to the customer servicedomain, questions 302 related to the setting domain, and questions 303related to the weather domain.

As a result, the question classification module 121 may input a user'squestion into the question classification model 310, and acquire adomain related to the user's question.

Then, the question classification module 121 may select a chat-botmatched to the acquired domain as a chat-bot for providing a response tothe user's question.

For example, if a user's question that is “The Internet connection isnot working” is received, the question classification module 121 mayinput the user's question into the question classification model 310,and thereby determine a domain (: a customer service domain) matched tothe user's question.

Then, the question classification module 121 may select a customerservice chat-bot matched to the customer service domain as a chat-botfor providing a response to the user's question.

FIG. 4 is a block diagram for illustrating an operation of an electronicapparatus according to an embodiment of the disclosure of acquiring aresponse of a selected chat-bot.

Referring to FIG. 4, the chat-bot management module 122 may acquireinformation on a chat-bot (ex. a customer service chat-bot) selected bythe question classification module 121.

Here, the chat-bot management module 122 may input a user's questioninto the selected chat-bot (the customer service chat-bot) among theplurality of chat-bots 410, 420, 430, etc.

As a result, a response of the customer service chat-bot for the user'squestion may be acquired as in FIG. 4.

FIG. 5A is a block diagram of a function information extraction moduleof an electronic apparatus according to an embodiment of the disclosureof extracting/selecting function information from a chat-bot's response.

Referring to FIG. 5A, the aforementioned function information extractionmodule 123 may include a formatting module 510, a function extractor520, a function selector 530, etc.

The formatting module 510 is a module for converting a chat-bot'sresponse for a user's question into the form of a text.

In case a chat-bot's response is a text, an operation of the formattingmodule 510 is not necessary, but in case a chat-bot's response is animage or a video, the formatting module 510 may acquire a text from theimage or the video.

For this, the formatting module 510 may recognize at least one textincluded in an image/a video through technologies such as opticalcharacter recognition (OCR), etc., but the disclosure is not limitedthereto.

The function extractor 520 is a module for extracting information on atleast one function from a text.

The function extractor 520 may acquire words/sentences matched to atleast one function from a text by using prestored words/sentences thatindicate each of various functions.

For this, the function extractor 520 may vectorize each word/sentenceincluded in a text and compare them with the vectors of the prestoredwords/sentences, but the disclosure is not limited thereto.

The function selector 530 is a module for selecting a function that canbe performed at the electronic apparatus 100.

The function selector 530 may select a function that can be performed atthe electronic apparatus 100 among at least one function extracted fromthe function extractor 520.

As an example, a list regarding functions that can be performed at theelectronic apparatus 100 may be stored in the memory 110.

Here, in case a plurality of functions were extracted through thefunction extractor 520, the function selector 530 may identify at leastone function that can be performed at the electronic apparatus 100 amongthe plurality of functions based on the list.

The function selector 530 may use a function selection model trained toselect a function for responding to a question among a plurality offunctions.

FIG. 5B is a diagram for illustrating an operation of an electronicapparatus according to an embodiment of the disclosure of selecting atleast one function from a plurality of extracted functions.

FIG. 5B is based on the assumption of a situation wherein a plurality offunctions 551 were extracted through the function extractor 520.

In this case, the function selector 530 may input the plurality ofextracted functions 551 into a function selection model 531.

In addition, the function selector 530 may input a list 552 regardingfunctions that can be performed at the electronic apparatus 100 and auser's question 553 into the function selection model 531.

Then, referring to FIG. 5B, the function selection model 531 maycalculate scores for each of the extracted functions 551 by using thelist 552 and the user's question 553.

The scores may be defined as complexly digitizing relevance to a user'squestion and operability at the electronic apparatus 100, for eachfunction.

For this, the function selection model 531 may be trained to identify afunction related to a response text that may follow a user's questionbased on a conversation generation technology. (ex. RNN). Also, thefunction selection model 531 may be trained to vectorize each functionthat can be performed at the electronic apparatus 100 and each of theinput (extracted) function, and calculate similarity.

Also, referring to FIG. 5B, the function selection model 531 may outputmobile data>turn on 551′ that is the function having the highestcalculated score among the extracted functions 551.

In case a function that can be performed at the electronic apparatus 100is not extracted from a chat-bot's response, the processor 120 mayimmediately provide the response.

For example, in case no function was extracted from a response, or afunction that can be performed at the electronic apparatus 100 was notextracted from a response, the processor 120 may output only theresponse in the form of a voice through the speaker.

FIG. 6 is a block diagram of a question generation module of anelectronic apparatus according to an embodiment of the disclosure ofgenerating a question requesting to perform an extracted/selectedfunction and using the question.

The question generation module 124 may generate a question related to afunction extracted/selected from the function information extractionmodule 123.

Referring to FIG. 6, the question generation module 124 may generate aquestion 611 requesting a function 551′ extracted/selected from thefunction information extraction module 123.

For this, the question generation module 124 may use a questiongeneration model 610 trained to convert an input word/sentence into aquestion text.

The question generation model 610 may be implemented in a form ofincluding an encoder and a decoder for changing the type of an inputword/sentence to a question sentence, but the disclosure is not limitedthereto.

Also, referring to FIG. 6, the generated question 611 may then be inputinto the question classification module 121.

Here, the question classification module 121 may select a chat-bot forresponding to the generated question 611 and/or providing a functionrelated to the generated question 611.

As a result, a chat-bot that can perform the function 551′ may beselected.

Then, the chat-bot management module 122 may input the generatedquestion 611 into the selected chat-bot (ex. a setting chat-bot) andacquire a response (Shall I turn on the mobile data?).

As described above, a response acquired according to a generatedquestion may include a question text inquiring about whether to performa function (mobile data>turn on) extracted/selected from the functioninformation extraction module 123.

In case it was identified that there is no chat-bot for responding to agenerated question among the plurality of chat-bots, a response for auser's question may be provided only based on the aforementionedresponse acquired in FIG. 4.

For example, in case the question classification module 121 input thegenerated question 511′ into the question classification model 310, andas a result, the customer service chat-bot that was already selected forresponding to a user's question (refer to FIG. 4) is selected again, theprocessor 120 may provide only the previous response of the customerservice chat-bot (refer to FIG. 4).

As another example, in case the question classification module 121 inputthe generated question 511′ into the question classification model 310,and as a result, no chat-bot is selected, the processor 120 may provideonly the previous response of the customer service chat-bot (refer toFIG. 4).

In case responses were acquired from each of the chat-bot selectedaccording to a user's question and the chat-bot selected according to agenerated question, the processor 120 may provide a response to theuser's question by using the acquired responses.

Here, the processor 120 may simply provide the acquired responsestogether, or the processor 120 may generate a combined response whereinthe responses are combined and provide the generated combined response.

FIG. 7 is a diagram for illustrating an operation of an electronicapparatus according to an embodiment of the disclosure of combiningresponses output from different chat-bots.

Referring to FIG. 7, the processor 120 may use a response generationmodel 710 trained to, if a plurality of responses are input, combine theinputs.

The response generation model 710 may be implemented by using modelstrained to perform summary for a text. In this case, if a plurality ofresponses are input, the response generation model 710 may summarize theentire text including the input responses and output a combinedresponse.

Alternatively, the response generation model 710 may be trained with thetwo responses and the combined response wherein the responses arecombined respectively as input/output training data.

Referring to FIG. 7, the processor 120 may input a response 711 in FIG.4 and a response 712 in FIG. 6 into the response generation model 710,and as a result, acquire a combined response 713. The combined response713 includes a question regarding whether to perform the mobiledata>turn on 551′ function.

Here, in case a user's request for performing the function is input, theprocessor 120 may perform the function (mobile data>turn on) through thechat-bot (ex. the setting chat-bot) that provided the response 712.

FIG. 8 is a block diagram of a detailed configuration of an electronicapparatus according to various embodiments of the disclosure.

Referring to FIG. 8, the electronic apparatus 100 may further include amicrophone 130, a speaker 140, a communication interface 150, a userinterface 160, a display 170, etc. other than the memory 110 and theprocessor 120.

The memory 110 is a component for storing an operating system (OS) forcontrolling the overall operations of the components of the electronicapparatus 100 and at least one instruction or data related to thecomponents of the electronic apparatus 100.

The memory 110 may include one or more of a non-volatile memory such asa ROM, a flash memory, etc., and it may also include a volatile memoryconsisting of a DRAM, etc. Also, the memory 110 may include a hard disk,a solid state drive (SSD), etc.

In the memory 110, artificial intelligence models such as a questionclassification model 310, a function selection model 531, a questiongeneration model 610, a response generation model 710, etc. may bestored.

Each artificial intelligence model may consist of, for example, aplurality of neural network layers. Each of the plurality of neuralnetwork layers has a plurality of weight values, and performs a neuralnetwork operation through an operation between the operation result ofthe previous layer and the plurality of weight values. The plurality ofweight values included by the plurality of neural network layers may beoptimized by the learning result of the artificial intelligence model.

Other than the above, the memory 110 may include an auto speechrecognition (ASR) model, a natural language understanding model, atext-to-speech (TTS) model, etc., and in addition to them, the memory110 may include artificial intelligence models having various functionsconstituting each chat-bot.

The processor 120 controls the overall operations of the electronicapparatus 100. The processor 120 may be connected with the memory 110and control the electronic apparatus 100.

For this, the processor 120 may include a central processing unit (CPU),a graphic processing unit (GPU), a neural processing unit (NPU), etc. interms of hardware, and the processor 120 may perform operations or dataprocessing related to control of the other components included in theelectronic apparatus 100.

The processor 120 may be implemented as a micro processing unit (MPU),or it may correspond to a computer wherein a random access memory (RAM)and a read only memory (ROM), etc. are connected with a CPU, etc.through a system bus.

The processor 120 may control not only hardware components included inthe electronic apparatus 100 but also one or more software modulesincluded in the electronic apparatus 100. Also, a result of theprocessor 120 of controlling software modules may be derived asoperations of the hardware components.

The processor 120 may consist of one or a plurality of processors. Here,the one or plurality of processors may be generic-purpose processorssuch as a CPU, an AP, etc., graphic-dedicated processors such as a GPU,a VPU, etc., or artificial intelligence-dedicated processors such as anNPU.

The one or plurality of processors perform control such that input datais processed according to a pre-defined operation rule or an artificialintelligence model stored in the memory. The pre-defined operation ruleor the artificial intelligence model are characterized in that they aremade through learning (training).

Here, being made through learning means that a learning algorithm isapplied to a plurality of learning data, and a pre-defined operationrule or an artificial intelligence model having a desired characteristicis thereby made. Such learning may be performed in an apparatus itselfwherein artificial intelligence according to the disclosure isperformed, or performed through a separate server/system.

A learning algorithm is a method of training a subject apparatus (e.g.,a robot) by using a plurality of learning data and thereby making thesubject apparatus make a decision or make prediction by itself. Asexamples of learning algorithms, there are supervised learning,unsupervised learning, semi-supervised learning, or reinforcementlearning, but learning algorithms in the disclosure are not limited tothe aforementioned examples excluding specified cases.

The microphone 130 is a component for receiving a user's voice. Themicrophone 130 includes at least one circuit for converting a user'svoice into an electronic audio signal.

The speaker 140 is a component for outputting a response/a question ofat least one chat-bot or assistant in the form of a voice. The speaker140 may include various components for converting an electronic audiosignal into a sound.

The communication interface 150 is a component for performingcommunication with one or more external electronic apparatuses, and itmay include a circuit.

The communication interface 150 may transmit and receive variousinformation with one or more external electronic apparatuses by usingcommunication protocols such as a Transmission Control Protocol/anInternet Protocol (TCP/IP), a User Datagram Protocol (UDP), a Hyper TextTransfer Protocol (HTTP), a Secure Hyper Text Transfer Protocol (HTTPS),a File Transfer Protocol (FTP), a Secure File Transfer Protocol (SFTP),a Message Queuing Telemetry Transport (MQTT), etc.

For this, the communication interface 150 may be connected with anexternal electronic apparatus based on a network implemented throughwired communication and/or wireless communication. Here, thecommunication interface 150 may be directly connected with an externalelectronic apparatus, but it may also be connected with an externalelectronic apparatus through one or more external servers (ex. anInternet Service Provider (ISP)) that provide a network.

A network may be a personal area network (PAN), a local area network(LAN), a wide area network (WAN), etc. according to the area or thescale, and it may be an Intranet, an Extranet, or the Internet, etc.according to the openness of the network.

Wireless communication may include any one or any combination ofcommunication methods such as long-term evolution (LTE), LTE Advance(LTE-A), 5th Generation (5G) mobile communication, code divisionmultiple access (CDMA), wideband CDMA (WCDMA), a universal mobiletelecommunications system (UMTS), a wireless broadband (WiBro), a globalsystem for mobile communications (GSM), time division multiple access(DMA), WiFi (Wi-Fi), WiFi Direct, Bluetooth, near field communication(NFC), Zigbee, etc.

Wired communication may include any one or any combination ofcommunication methods such as an Ethernet, an optical network, auniversal serial bus (USB), a Thunderbolt, etc. Here, the communicationinterface 150 may include a network interface or a network chipaccording to the aforementioned wired and wireless communicationmethods. Communication methods are not limited to the aforementionedexamples, but they may include communication methods that newly appearaccording to the development of technologies.

As an example, the communication interface 150 may perform communicationwith at least one external server.

In case a plurality of chat-bots are stored in a server, the processor120 may receive the responses of each chat-bot through the communicationinterface 150. An embodiment related thereto will be described laterthrough FIG. 9A.

Alternatively, any one or any combination of the aforementioned modules121, 122, 123, 124 may be stored in a server. In this case, a systemincluding the electronic apparatus 100 and the server 200 connected withthe electronic apparatus 100 through the communication interface 150 mayperform the operations of the aforementioned modules.

The user interface 160 is a component for receiving a user instructionand/or user information in various forms. The user interface 160 mayinclude various input interfaces such as a camera, a touch sensor, abutton, etc.

The display 170 is a component for displaying various contents orvarious user interfaces provided through the electronic apparatus 100.

The display 170 may visually provide services or responses providedthrough at least one chat-bot.

The display 170 may be implemented as an LED, a liquid crystal display(LCD), a plasma display panel (PDP), organic light emitting diodes(OLED), transparent OLED (TOLED), a micro LED, etc., but is not limitedthereto.

The display 170 may be implemented in the form of a touch screen thatcan detect a user's touch operation, and it may also be implemented as aflexible display that can be folded or bent.

FIG. 9A is a block diagram for illustrating an operation of anelectronic apparatus of using a plurality of chat-bots stored in aserver according to an embodiment of the disclosure.

FIG. 9A assumes a case wherein a plurality of chat-bots are stored in aserver 200. In FIG. 9A, the server 200 may input a question into eachchat-bot through a chat-bot management module 221, and acquire aresponse through each chat-bot.

As an example, in case the question classification module 121 selectedthe chat-bot 1 as a user's question was input into the electronicapparatus 100, the electronic apparatus 100 may transmit information onthe selected chat-bot 1 and the user's question to the server 200.

In this case, the server 200 may acquire a response for the user'squestion through the chat-bot 1, and transmit the response to theelectronic apparatus 100.

Here, the electronic apparatus 100 may generate a question (the questiongeneration module 124) by using the response received from the server200, and extract/select a function (the function information extractionmodule 123) from the generated question.

Then, the electronic apparatus 100 may select a chat-bot 2 that willprovide a response to the generated question through the questionclassification module 121.

Here, the electronic apparatus 100 may transmit information on theselected chat-bot 2 and the generated question to the server 200.

Then, when a response of the chat-bot 2 for the generated question isreceived from the server 200, the electronic apparatus 100 may combinethe responses of the chat-bot 1 and the chat-bot 2 and provide theresponse.

FIG. 9B is a block diagram for illustrating an operation of anelectronic apparatus of selectively using assistants stored in eachserver according to an embodiment of the disclosure.

FIG. 9B assumes a case wherein the electronic apparatus 100 performscommunication with a plurality of servers 200-1, 2, 3 providing servicesbased on different assistants.

Here, each of the assistants stored in the servers 200-1, 2, 3 mayrespectively include multi chat-bots.

The server 200-1 may manage the services (responses, functions, etc.) ofthe Assistant 1 through a chat-bot management module 221-1, the server200-2 may manage the services of the Assistant 2 through a chat-botmanagement module 221-2, and the server 200-3 may manage the services ofthe Assistant 3 through a chat-bot management module 221-3.

In the case of FIG. 9B, the question classification module 121 may use aclassification model trained to determine at least one assistant forresponding to an input question.

As an example, as a user's question is input into the electronicapparatus 100, the question classification module 121 may select theAssistant 1 as an assistant for responding to the user's question.

In this case, the electronic apparatus 100 may transmit information onthe selected Assistant 1 and the user's question to the server 200-1.

In this case, the server 200-1 may acquire a response for the user'squestion through the Assistant 1, and transmit the response to theelectronic apparatus 100.

Here, the electronic apparatus 100 may generate a question (the questiongeneration module 124) by using the response received from the server200, and extract/select a function from the generated question (thefunction information extraction module 123).

Then, the electronic apparatus 100 may select the Assistant 2 to providea response to the generated question through the question classificationmodule 121.

Here, the electronic apparatus 100 may transmit information on theselected Assistant 2 and the generated question to the server 200.

Then, when the response of the Assistant 2 for the generated question isreceived from the server 200, the electronic apparatus 100 may combinethe responses of the Assistant 1 and the Assistant 2, and provide thecombined response.

As described above, the electronic apparatus 100 according to thedisclosure may be constituted to not only combine responses/functions ofa plurality of chat-bots and provide them, but also combineresponses/functions of a plurality of assistants and provide them.

A control method of an electronic apparatus according to the disclosureis described with reference to FIG. 10 to FIG. 11 below.

FIG. 10 is a flowchart of a control method of an electronic apparatusaccording to an embodiment of the disclosure.

Referring to FIG. 10, in the control method according to the disclosure,a user's question may be input into a question classification modeltrained to determine a chat-bot for responding to a question among aplurality of chat-bots, and a first chat-bot for responding to theuser's question may be selected among a plurality of chat-bots inoperation S1010.

Then, a first response for the user's question may be acquired throughthe selected first chat-bot in operation S1020.

Through a question classification model, a first domain related to atext included in the user's question may be identified among a pluralityof domains.

Here, based on information on the plurality of domains respectivelymapped to the plurality of chat-bots, a first chat-bot mapped to theidentified first domain may be selected among the plurality ofchat-bots.

Then, in the control method, a question requesting to perform a functionincluded in the first response may be generated in operation S1030.

In case information on a function that can be performed at theelectronic apparatus is included in the first response, a questionrequesting to perform the function may be generated.

As an example, in case information on a function was acquired from theacquired first response, it may be determined whether the function is afunction that can be performed at the electronic apparatus. Here, incase the function is a function that can be performed at the electronicapparatus, a question requesting to perform the function may begenerated.

As another example, in case information on a plurality of functions wasacquired from the first response, at least one function that can beperformed at the electronic apparatus may be identified among theplurality of functions based on a list regarding functions that can beperformed at the electronic apparatus.

Then, a question requesting to perform the identified function may begenerated.

As an additional example, a case is assumed, wherein a functionselection model trained to, if information on a plurality of functionsis input, select a function corresponding to a question among theplurality of functions is included in the memory of the electronicapparatus.

In this case, in the control method, the information on the plurality offunctions acquired from the first response, the list regarding functionsthat can be performed at the electronic apparatus, and the user'squestion may be input into the function selection model.

As a result, at least one function that corresponds to the user'squestion and can be performed at the electronic apparatus may beidentified among the plurality of functions acquired from the firstresponse.

Meanwhile, in case information on functions that can be performed at theelectronic apparatus is not included in the acquired first response, aquestion may not be generated, and a response for the user's questionmay be provided just based on the first response.

In case a question was generated through the operation S1030, in thecontrol method, the generated question may be input into the questionclassification model, and a second chat-bot for responding to thegenerated question may be selected among the plurality of chat-bots inoperation S1040.

In this case, a second domain related to a text included in thegenerated question may be identified among the plurality of domainsthrough the question classification model.

Then, based on the information on the plurality of domains respectivelymapped to the plurality of chat-bots, a second chat-bot mapped to theidentified second domain may be selected among the plurality ofchat-bots.

In case it was identified that there is no chat-bot for responding tothe generated question among the plurality of chat-bots, a response forthe user's question may be provided based on the first response.

In case the second chat-bot was selected in the operation S1040, in thecontrol method, a second response for the question previously generatedmay be acquired through the selected second chat-bot in operation S1050.

Then, based on the first response and the second response, a responsefor the user's question may be provided in operation S1060.

Based on the first response and the second response, a combined responseincluding a question regarding whether to perform the function includedin the first response may be generated.

Then, the generated combined response may be provided. Here, thecombined response may be output through the speaker in the form of avoice.

Here, if a user's request for performing the function is input as thecombined response is provided, the function may be performed through thesecond chat-bot.

FIG. 11 is a flowchart of a control method of an electronic apparatusaccording to another embodiment of the disclosure.

Referring to FIG. 11, if a user's question is input in operation S1105,a chat-bot to respond to the user's question may be selected, and afirst response of the chat-bot may be acquired in operation S1110.

Here, a question classification model trained to select a chat-bot forresponding to a question may be used.

Here, it may be determined whether information on a function that can beperformed at the electronic apparatus exists in the acquired response inoperation S1115.

In case there is no information on a function that can be performed atthe electronic apparatus in the acquired response in operation S1115-N,a first response may simply be provided in operation S1120.

In contrast, in case there is information on a function that can beperformed at the electronic apparatus in the acquired response inoperation S1115-Y, a question requesting the function may be generatedin operation S1125.

In case there is information on a plurality of functions in the acquiredresponse, one of the functions may be selected by using a list offunctions that can be performed at the electronic apparatus and theuser's question. Then, a question requesting the selected function maybe generated.

When a question is generated, it may be identified whether there is achat-bot to perform the function related to the question in operationS1130.

By inputting the generated question into the aforementioned questionclassification model, a chat-bot to perform the function may beselected.

In case no chat-bot is identified/selected through the questionclassification model in operation S1130-N, only the aforementioned firstresponse may be provided in operation S1120.

In contrast, in case at least one chat-bot is identified/selectedaccording to the generated question in operation S1130-Y, a secondresponse for the generated question may be acquired through the chat-botin operation S1135.

Then, a combined response including the question regarding whether toperform the function may be provided based on the first response and thesecond response in operation S1140.

When the question is provided, it may be determined whether the useragrees to perform the function in operation S1145.

Here, in case the user agrees to perform the function in operationS1145-Y, the function may be performed in operation S1150 through thechat-bot identified in the operation S1130.

In contrast, in case the user does not agree to perform the function inoperation S1145-N, the function is not performed.

The control method of an electronic apparatus described through FIG. 9to FIG. 10 can be performed through the electronic apparatus 100illustrated and described through FIG. 2 and FIG. 8.

Alternatively, the control method of an electronic apparatus describedthrough FIG. 9 to FIG. 10 can be performed through a system includingthe electronic apparatus 100 and at least one external apparatus (ex. aserver).

The various embodiments described above may be implemented in arecording medium that can be read by a computer or an apparatus similarto a computer, by using software, hardware, or a combination thereof.

According to implementation by hardware, the embodiments described inthe disclosure may be implemented by using any one or any combination ofapplication specific integrated circuits (ASICs), digital signalprocessors (DSPs), digital signal processing devices (DSPDs),programmable logic devices (PLDs), field programmable gate arrays(FPGAs), processors, controllers, micro-controllers, microprocessors, oran electronic unit for performing various functions.

In some cases, the embodiments described in this specification may beimplemented as the processor itself. According to implementation bysoftware, the embodiments such as procedures and functions described inthis specification may be implemented as separate software modules. Eachof the aforementioned software modules may perform at least one functionand operation described in this specification.

Computer instructions for performing processing operations at theelectronic apparatus 100 according to the aforementioned variousembodiments of the disclosure may be stored in a non-transitorycomputer-readable medium. Computer instructions stored in such anon-transitory computer-readable medium make the processing operationsat the electronic apparatus 100 according to the aforementioned variousembodiments performed by the aforementioned machine, when theinstructions are executed by the processor of the machine.

A non-transitory computer-readable medium refers to a medium that storesdata semi-permanently, and is readable by machines, but not a mediumthat stores data for a short moment such as a register, a cache, and amemory. The aforementioned various applications or programs may beprovided while being stored in a non-transitory computer readable-mediumsuch as a CD, a DVD, a hard disk, a blue-ray disk, a USB, a memory card,a ROM and the like.

Also, while embodiments of the disclosure have been shown and described,the disclosure is not limited to the aforementioned embodiments, and itis apparent that various modifications may be made by those havingordinary skill in the technical field to which the disclosure belongs,without departing from the gist of the disclosure as claimed by theappended claims. Further, it is intended that such modifications are notto be interpreted independently from the technical idea or prospect ofthe disclosure.

What is claimed is:
 1. An electronic apparatus comprising: at least onememory storing instructions, a plurality of chat-bots for responding toa plurality of questions, and a question classification model trained toidentify a chat-bot among the plurality of chat-bots for responding toan input question; and a processor configured to execute theinstructions to: input the input question into the questionclassification model, the question classification model outputting afirst chat-bot among the plurality of chat-bots for responding to theinput question, acquire a first response for the input question, throughthe outputted first chat-bot, based on the acquired first responsecomprising information of a function that can be performed at theelectronic apparatus, generate a question requesting to perform thefunction, input the generated question into the question classificationmodel, the question classification model outputting a second chat-botamong the plurality of chat-bots for responding to the generatedquestion, acquire a second response for the generated question, throughthe outputted second chat-bot, and provide a combined response to theinput question, based on the acquired first response and the acquiredsecond response.
 2. The electronic apparatus of claim 1, wherein the atleast one memory further stores information of a plurality of domainsrespectively mapped to the plurality of chat-bots, and the processor isfurther configured to execute the instructions to: through the questionclassification model, identify a first domain among the plurality ofdomains that is related to a text included in the input question, andbased on the information of the plurality of domains respectively mappedto the plurality of chat-bots, select the first chat-bot among theplurality of chat-bots that is mapped to the identified first domain. 3.The electronic apparatus of claim 2, wherein the processor is furtherconfigured to execute the instructions to: through the questionclassification model, identify a second domain among the plurality ofdomains that is related to a text included in the generated question,and based on the information of the plurality of domains respectivelymapped to the plurality of chat-bots, select the second chat-bot amongthe plurality of chat-bots that is mapped to the identified seconddomain.
 4. The electronic apparatus of claim 1, wherein the processor isfurther configured to execute the instructions to, based on the acquiredfirst response not comprising the information of the function that canbe performed at the electronic apparatus, provide a response to theinput question, based on the acquired first response.
 5. The electronicapparatus of claim 1, wherein the at least one memory further stores alist of functions that can be performed at the electronic apparatus, andthe processor is further configured to execute the instructions to:based on the acquired first response comprising information of aplurality of functions, identify at least one function among theplurality of functions that can be performed at the electronicapparatus, based on the list, and generate the question requesting toperform the identified at least one function.
 6. The electronicapparatus of claim 5, wherein the at least one memory further stores afunction selection model trained to, based on information of theplurality of functions being input, select one or more functions amongthe plurality of functions that corresponds to the input question, andthe processor is further configured to execute the instructions to inputthe information of the plurality of functions included in the acquiredfirst response, the list, and the input question into the functionselection model, the function selection model outputting the one or morefunctions among the plurality of functions that corresponds to the inputquestion and can be performed at the electronic apparatus.
 7. Theelectronic apparatus of claim 1, wherein the processor is furtherconfigured to execute the instructions to, based on identifying thatthere is not one among the plurality of chat-bots for responding to thegenerated question, provide a response to the input question, based onthe acquired first response.
 8. The electronic apparatus of claim 1,wherein the processor is further configured to execute the instructionsto: based on the acquired first response and the acquired secondresponse, generate the combined response including a question regardingwhether the function can be performed, provide the generated combinedresponse, and based on a request for performing the function being inputas the combined response is provided, perform the function, through thesecond chat-bot.
 9. A control method of an electronic apparatus, thecontrol method comprising: inputting an input question into a questionclassification model trained to identify a chat-bot among a plurality ofchat-bots for responding to the input question, the questionclassification model outputting a first chat-bot among the plurality ofchat-bots for responding to the input question; acquiring a firstresponse for the input question, through the outputted first chat-bot;based on the acquired first response comprising information of afunction that can be performed at the electronic apparatus, generating aquestion requesting to perform the function; inputting the generatedquestion into the question classification model, the questionclassification model outputting a second chat-bot among the plurality ofchat-bots for responding to the generated question; acquiring a secondresponse for the generated question, through the outputted secondchat-bot; and providing a combined response to the input question, basedon the acquired first response and the acquired second response.
 10. Thecontrol method of claim 9, wherein the inputting the input question intothe question classification model comprises: through the questionclassification model, identifying a first domain among a plurality ofdomains that is related to a text included in the input question, theplurality of domains respectively mapped to the plurality of chat-bots;and based on the information of the plurality of domains respectivelymapped to the plurality of chat-bots, selecting the first chat-bot amongthe plurality of chat-bots that is mapped to the identified firstdomain.
 11. The control method of claim 10, wherein the inputting thegenerated question into the question classification model comprises:through the question classification model, identifying a second domainamong the plurality of domains that is related to a text included in thegenerated question; and based on the information of the plurality ofdomains respectively mapped to the plurality of chat-bots, selecting thesecond chat-bot among the plurality of chat-bots that is mapped to theidentified second domain.
 12. The control method of claim 9, furthercomprising, based on the acquired first response not comprising theinformation of the function that can be performed at the electronicapparatus, providing a response to the input question, based on theacquired first response.
 13. The control method of claim 9, furthercomprising: based on the acquired first response comprising informationof a plurality of functions, identifying at least one function among theplurality of functions that can be performed at the electronicapparatus, based on a list of functions that can be performed at theelectronic apparatus; and generating the question requesting to performthe identified at least one function.
 14. The control method of claim13, wherein the identifying the at least one function among theplurality of functions that can be performed at the electronic apparatuscomprises inputting the information of the plurality of functionsincluded in the acquired first response, the list, and the inputquestion into a function selection model trained to, based oninformation of the plurality of functions being input, select one ormore functions among the plurality of functions that corresponds to theinput question, the function selection model outputting the one or morefunctions among the plurality of functions that corresponds to the inputquestion and can be performed at the electronic apparatus.
 15. Thecontrol method of claim 9, further comprising, based on identifying thatthere is not one among the plurality of chat-bots for responding to thegenerated question, providing a response to the input question, based onthe acquired first response.